Nonsleepy Sleep Disordered Breathing and Cardiovascular Disease

Man sleeping and snoring in bed
Man sleeping and snoring in bed
What is the relationship between non-sleepy sleep-disordered breathing and cardiovascular disease, and which nocturnal hypoxia parameter most strongly reflects this association?

Nonsleepy sleep-disordered breathing (SDB) is prevalent and independently associated with the risk for cardiovascular disease (CVD), according to a study in Nature and Science of Sleep.

The relationship between SDB, an increasingly recognized clinical subtype, and CVD has yet to be elucidated. Researchers in China explored this relationship in a prospective, multisite, cross-sectional cohort study evaluating the relationship between nonsleepy SDB and CVD, which also sought to determine which nocturnal hypoxia parameter most strongly reflects the association between SDB and CVD. Eligible participants were enrolled from the general population in China from April 9, 2021, to May 18, 2021.

The 3626 participants studied (median age, 55 years; 30.2% male) used of a type IV wearable intelligent sleep monitor (from CloudCare Healthcare). Monitoring parameters included 3% or 4% oxygen desaturation index (ODI), nocturnal mean oxygen saturation (meanSpO2), lowest nocturnal oxygen saturation (minSpO2), and time spent with oxygen saturation less than 90%.

An ODI at least 7.0 events per hour was used to indicate SDB. A score of greater than 10 on the Epworth Sleepiness Scale indicated excessive daytime sleepiness, and an Epworth Sleepiness Scale score of up to 10 and an ODI at least 7.0 events per hour indicated nonsleepy SDB.

Among all study participants, 110 had excessive daytime sleepiness and 3516 did not. Overall, 1114 participants (30.7%) had SDB, of whom 96.5% (1075) had SDB without excessive daytime sleepiness, or the nonsleepy SDB subtype.

The ODI was significantly associated with CVD (odds ratio [OR] 1.052; 95% CI, 1.042-1.064 for all study participants; OR 1.036; 95% CI, 1.019-1.053 for participants with SDB) in the unadjusted logistic regression model. This association was attenuated but still significant after adjustment for excessive daytime sleepiness and other confounders.

The fully adjusted model showed that ODI was independently associated with increased odds of CVD (OR 1.017; 95% CI, 1.004-1.030 for all study participants; OR 1.024; 95% CI, 1.005-1.044 for individuals with SDB) regardless of the presence of excessive daytime sleepiness, and no significant interaction was found between excessive daytime sleepiness and ODI (P >.05). Excessive daytime sleepiness was not significantly associated with CVD among the different models.

Oxygen desaturation index and mean SpO2 were associated significantly with CVD (OR 1.034; 95% CI, 1.017-1.052 and OR 0.900; 95% CI, 0.845-0.959, respectively) in adjusted models. In partial and fully adjusted models, only ODI was correlated significantly with CVD (OR 1.024; 95% CI, 1.005-1.043 and OR 1.023; 95% CI, 1.003-1.043, respectively).

A nonlinear association was observed between ODI and CVD, in which the likelihood of CVD increased with an ODI of at least 10 events per hour. A markedly increasing trend was found with ODI of at least 20 events per hour (reference ODI=7.0 events/hour).

Among participants who had nonsleepy SDB, subgroup analyses according to sex and body mass index (BMI) showed that ODI was associated significantly with CVD in men and participants who had a BMI of at least 25 (OR 1.029; 95% CI, 1.002-1.056; OR 1.036; 95% CI, 1.007-1.065, respectively). No significant interaction effects occurred among ODI and sex, age, BMI, or diabetes (P >.05 for all interactions).

Study limitations include the cross-sectional design and inability to assess the relationship between nonsleepy SDB and incident CVD. Also, the assessment of excessive daytime sleepiness was subjective, and the diagnoses of coronary artery disease, heart failure, or stroke were obtained by self-report. Furthermore, type IV wearable sleep monitoring may not be precise for evaluating SDB, and the results may be potentially biased.

“In the general population, primary health care providers and health care policy makers should place importance on the identification of patients with the nonsleepy SDB subtype,” stated the researchers. “ODI, an easily extracted indicator from a type IV sleep monitor, most strongly reflected the association between nonsleepy SDB and CVD.”


Wang L, Ou Q, Shan G, et al. Independent association between oxygen desaturation index and cardiovascular disease in non-sleepy sleep-disordered breathing subtype: a Chinese community-based study. Nat Sci Sleep. 2022;14:1397-1406. doi:10.2147/NSS.S370471